Résumé
Introduction: Lumbricals are the small, worm-like, intrinsic muscles responsible for performing the precision pinch movements of the hand. These are quite unique in their position owing to movable proximal and distal tendon attachments. Purpose of the study: The aim of the study was to identify anomalies of lumbrical muscle present in the Sri Lankan people. Materials and Methods: A sample of 39 formalin preserved cadaveric human hands were subjected to the gross morphological study. Results: It was encountered that 59% of the lumbricals were normal in proximal and distal attachments whereas the rest of the lumbicals (41%) indicated the morphological variations. Among the hands, unipennate third lumbrical was seen in 7.7% (Left-15.7%: Right 0%) and unipennate fourth lumbrical was seen in 5.1% (Left10.5%: Right 0%). The bipennate second lumbrical was seen in 5.1% (Left 5.3%: Right 5.1%). The 10.3% of split insertion was encountered in third lumbricals (Left 10.5%: Right 10%) as well as in fourth lumbricals (Left 5.3%: Right 15%). The third lumbrical insertion on the medial side of the middle finger was seen in 2.5% (Left 5.3%: Right 0%). Conclusion: The left hand is having more lumbrical variations than the right hand of the subjected human cadavers. The most common variation site is the insertion site. The variants are numerous in third and fourth lumbricals. The most common type of variation is the split insertion.
Résumé
SUMMARY: Sex estimation from human skeletal remains is of vital importance in the buildup of a biological profile of an individual in medico-legal and bioarchaeological studies. The present study is focused on the estimation of sex from osteometric measurements of the complete femur and its fragmentary parts, and the development of a web based application related to this. Fifteen osteometric measurements were taken from 78 dry cadaveric femurs from the Faculty of Medicine, University of Kelaniya. Using R software, linear discriminant analysis and logistic regression methods were applied to build classification models with the help of the application of a stepwise procedure, to identify the best combination of measurements to estimate the sex of the femur. A cross-validation method was applied to estimate the predictive accuracy of each model. Since the linear discriminant analysis model gave more predictive accuracy than the regression model, we suggest using linear discriminant analysis to estimate the sex using osteometric measurements of the femur. From the whole femur measurements, a formula to determine sex was developed with highest total accuracy of 83 % using four parameters; epicondylar breadth, anteroposterior mid-shaft diameter, bi-trochanter length, and maximum shaft diameter. Similarly, measurements of transverse head diameter and bi-trochanter length with a total accuracy of 76 % for the proximal part of the femur, measurements of anteroposterior mid-shaft diameter with a total accuracy of 77 % for the mid-shaft, and measurements of epicondylar breadth and maximum length of the lateral condyle with a total accuracy of 70 % for the distal part of the femur were identified as significant discriminants to determine sex, and formulae were written accordingly. Average accuracy ranged from 83 % to 70 %, with male accuracy slightly higher than that of females. A web application to estimate the sex of femur using these formulae was developed and this will be of great importance for forensic medicine and bio-archaeological research in Sri Lanka.
RESUMEN: La estimación del sexo a partir de restos óseos humanos en los estudios médico-legales y bioarqueológicos es de vital importancia en la construcción de un perfil biológico de un individuo. El objetivo de este estudio fue la estimación del sexo a partir de medidas osteométricas del fémur completo y sus partes fragmentarias, y el desarrollo de una aplicación web relacionada con esto. Se tomaron quince medidas osteométricas de 78 fémures cadavéricos secos de la Facultad de Medicina de la Universidad de Kelaniya. Utilizando el software R, se aplicaron métodos de análisis discriminante lineal y regresión logística para construir modelos de clasificación con la aplicación de un procedimiento por pasos, para identificar la mejor combinación de medidas y estimar el sexo a partir del fémur. Se aplicó un método de validación cruzada para estimar la precisión predictiva de cada modelo. Dado que el modelo de análisis discriminante lineal proporcionó una mayor precisión predictiva que el modelo de regresión, sugerimos su utilización para estimar el sexo mediante mediciones osteométricas del fémur. A partir de las mediciones del fémur completo, se desarrolló una fórmula para determinar el sexo con la mayor precisión total del 83 % utilizando cuatro parámetros; anchura del epicóndilo, diámetro anteroposterior del tercio medio de la diáfisis, longitud bitrocánter y diámetro máximo de la diáfisis. De manera similar, utilizamos las mediciones del diámetro transversal de la cabeza del fémur y la longitud del bitrocánter con una precisión del 76 % para la parte proximal del hueso, las mediciones del diámetro anteroposterior del tercio medio de la diáfisis se obtuvo con una precisión del 77 %. El ancho del epicóndilo y la longitud máxima del cóndilo lateral con una precisión del 70 % para la parte distal del fémur se identificaron como discriminantes significativos para determinar el sexo y se escribieron fórmulas. La precisión promedio osciló entre el 83 % y el 70 %, siendo la precisión en los hombres ligeramente superior al de las mujeres. Se desarrolló una aplicación web para estimar el sexo del fémur utilizando estas fórmulas y creemos será importante para la medicina forense y la investigación bioarqueológica en Sri Lanka.